---
title: "Pilot Data 2020"
output:
flexdashboard::flex_dashboard:
orientation: columns
social: menu
source_code: embed
vertical_layout: scroll
theme: spacelab
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(rio)
library(here)
library(colorblindr)
library(gghighlight)
library(forcats)
library(ggrepel)
library(gt)
library(knitr)
library(kableExtra)
library(reactable)
library(plotly)
opts_chunk$set(echo = FALSE,
fig.width = 5,
fig.height = 6)
theme_set(theme_minimal(base_size = 8))
outcome <- import(here("data", "client_data_outcome.sav"),
setclass = "tbl_df") %>%
characterize() %>%
janitor::clean_names()
rm_prge <- import(here("data", "repeated_measures_prge.sav"),
setclass = "tbl_df") %>%
characterize() %>%
janitor::clean_names()
head(outcome)
head(rm_prge)
prge_class_worse <- import(here("data", "prge_class.xlsx"),
setclass = "tbl_df")
prge_class_stress <- import(here("data", "prge_class_stress.xlsx"),
setclass = "tbl_df")
prge_pcss <- import(here("data", "pcss_prge.xlsx"),
setclass = "tbl_df")
rm_drkat <- import(here("data", "drkat_rm.xlsx"),
setclass = "tbl_df") %>%
janitor::clean_names()
head(rm_drkat)
brief_data <- import(here("data", "brief_pilot_data.xlsx"),
setclass = "tbl_df") %>%
janitor::clean_names()
head(brief_data)
falo_rm <- import(here("data", "falo_rm.xlsx"),
setclass = "tbl_df") %>%
janitor::clean_names()
```
# PRGE Outcome
Column {.tabset data-width=650}
-----------------------------------------------------------------------
```{r outcome measures data organization, include=FALSE}
head(outcome)
brief <- outcome %>%
filter(client == "PRGE") %>%
select(1, c(16:31))
brief_prge <- brief %>%
select(client, brief_eri_pre_self, brief_eri_post_self, brief_eri_pre_inf, brief_eri_post_inf)
brief_tidy <- brief_prge %>%
rename("Self Pre ERI" = brief_eri_pre_self,
"Self Post ERI" = brief_eri_post_self,
"Parent Pre ERI" = brief_eri_pre_inf,
"Parent Post ERI" = brief_eri_post_inf) %>%
pivot_longer(
cols = c(2:5),
names_to = "measure",
values_to = "score"
)
prge_brief_parent <- brief_data %>%
filter(client == "PRGE") %>%
select(client, 8, 9, 16, 17) %>%
rename("SM Pre" = self_monitor_pre_parent,
"SM Post" = self_monitor_post_parent,
"EC Pre" = emotional_control_pre_parent,
"EC Post" = emotional_control_post_parent) %>%
pivot_longer(
cols = c(2:5),
names_to = "measure",
values_to = "score"
)
prge_parent <- c("SM Pre",
"SM Post",
"EC Pre",
"EC Post")
class <- outcome %>%
filter(client == "PRGE") %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post)
class_tidy <- class %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
symptoms <- outcome %>%
filter(client == "PRGE") %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit <- outcome %>%
filter(client == "PRGE") %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r outcome plots, include=FALSE}
#geom_rect(aes(xmin = -Inf, xmax = Inf, ymin = 65, ymax = 100),
#fill = "lightgreen") + #insert before geom_col
prge_brief <- c("Self Pre ERI",
"Self Post ERI",
"Parent Pre ERI",
"Parent Post ERI")
class_positions <- c("Pre Score", "Post Score")
pcss_positions <- c("Difficulty Remembering Post",
"Difficulty Remembering Pre",
"Difficulty Concentrating Post",
"Difficulty Concentrating Pre",
"Feeling Foggy Post",
"Feeling Foggy Pre",
"Feeling Slow Post",
"Feeling Slow Pre")
hit_positions <- c("Pre Score", "Post Score")
p1 <- ggplot(brief_tidy, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = prge_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Emotion Regulation Index",
caption = "T-scores Above 65 are Clinically Significant")
prge_parent_graph <- ggplot(prge_brief_parent, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = prge_parent) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Parent Responses to the Self-Monitor and Emotional Control Scales",
caption = "T-scores Above 65 are Clinically Significant")
prge_parent_graph
p1
p2 <- ggplot(class_tidy, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
p2
p3 <- ggplot(symptoms, aes(measure, score)) +
geom_hline(yintercept = 30,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
coord_flip() +
geom_text(aes(measure, score, label = score),
nudge_y = -0.5,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
p3
p3a <- ggplot(hit, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Impact Daily Functioning")
p3a
head(prge_class_worse)
head(prge_class_stress)
prge_class_worse_tidy <- prge_class_worse %>%
pivot_longer(
cols = c(`Pre-Test`, `Post-Test`),
names_to = "Assessment",
values_to = "Response"
)
class_1 <- c("Easily bothered by lights/screens or noise",
"Tiring easily during homework",
"Tiring easily during the school day",
"Headaches interfering with homework",
"Headaches interfering with classwork",
"Easily distracted during homework",
"Easily distracted during classwork",
"Trouble reading",
"Trouble remembering what was studied",
"Difficulty studying for tests or quizzes",
"Homework taking longer",
"In class, work taking longer",
"Difficulty understanding new material",
"Difficulty taking notes")
class_1_resp <- c("A lot worse",
"Somewhat worse",
"A little worse",
"Not worse")
prge_class_worse_tidy$Assessment <- factor(prge_class_worse_tidy$Assessment, levels = c("Pre-Test", "Post-Test"))
prge_class_worse_plot <- ggplot(prge_class_worse_tidy, aes(`Question`, `Response`)) +
geom_line(aes(group = `Question`), color = "gray40") +
geom_point(aes(color = `Assessment`)) +
coord_flip() +
scale_x_discrete(limits = class_1) +
scale_y_discrete(limits = class_1_resp) +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text.x = element_text(size = 10, angle = 90),
axis.text.y = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10),
legend.title = element_text(size = 10),
legend.text = element_text(size = 8)) +
labs(x = "",
y = "",
title = "CLASS Responses",
subtitle = "Questions 1-14")
prge_class_worse_plot
head(prge_class_stress)
prge_class_stress_tidy <- prge_class_stress %>%
pivot_longer(
cols = c(`Pre-Test`, `Post-Test`),
names_to = "Assessment",
values_to = "Response"
)
class_2 <- c("Stressed out about your grades dropping",
"More stressed out/overwhelmed with the schoolwork piling up",
"Not having enough support at home from parents/siblings",
"Not having enough support from teachers",
"Not being allowed to play sports/recreation",
"Missing time with friends and/or social activities")
class_2_resp <- c("Very stressful",
"Moderately stressful",
"A little stressful",
"Not stressful")
prge_class_stress_tidy$Assessment <- factor(prge_class_stress_tidy$Assessment, levels = c("Pre-Test", "Post-Test"))
prge_class_stress_plot <- ggplot(prge_class_stress_tidy, aes(`Question`, `Response`)) +
geom_line(aes(group = `Question`), color = "gray40") +
geom_point(aes(color = `Assessment`)) +
coord_flip() +
scale_x_discrete(limits = class_2) +
scale_y_discrete(limits = class_2_resp) +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10),
legend.title = element_text(size = 8),
legend.text = element_text(size = 8)) +
labs(x = "",
y = "",
title = "CLASS Responses",
subtitle = "Questions 15-20")
prge_class_stress_plot
head(prge_pcss)
prge_pcss_table <- prge_pcss %>%
reactable(
columns = list(
`Pre Test` = colDef(name = "Pre-Test"),
`Post Test` = colDef(name = "Post-Test")),
pagination = FALSE,
striped = TRUE,
outlined = TRUE,
compact = TRUE,
highlight = TRUE,
bordered = TRUE,
searchable = TRUE,
height = 600,
width = 500)
```
### BRIEF Client-Parent Responses
```{r prge brief, include=TRUE}
p1
```
### BRIEF Parent Responses
```{r prge parent brief, include=TRUE}
prge_parent_graph
```
### CLASS 1
```{r prge class 1, include=TRUE, fig.width=8}
prge_class_worse_plot
```
### CLASS 2
```{r prge class 2, include=TRUE, fig.width=8}
prge_class_stress_plot
```
### PCSS
```{r prge pcss, include=TRUE}
prge_pcss_table
```
### HIT
```{r prge hit, include=TRUE}
p3a
```
Column {data-width=350}
-----------------------------------------------------------------------
### Client Demographics
```{r, include=FALSE}
head(outcome)
demo_prge <- outcome %>%
filter(client == "PRGE") %>%
select(2:5)
head(demo_prge)
prge_table <- demo_prge %>%
gt() %>%
cols_label(sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression or Anxiety") %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
prge_table
```
```{r prge table, include=TRUE}
prge_table
```
# PRGE Repeated
Column {.tabset data-width=650}
-----------------------------------------------------------------------
### Status Tracking
```{r repeated measures data cleaning, include=FALSE}
head(rm_prge)
track <- rm_prge %>%
select(session, status)
p4 <- ggplot(track, aes(session, status)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 6),
breaks = c(1, 2, 3, 4, 5, 6)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Times Required to Reread Content",
title = "Status Tracking Goal")
p4
effort_data <- rm_prge %>%
select(session, effort)
p5 <- ggplot(effort_data, aes(session, effort)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effort During Reading",
title = "Perceived Effort While Reading",
caption = "1 = No Effort\n 2 = A little Effort\n 3 = Somewhat Effortful\n 4 = Quite Effortful\n 5 = Extremely Effortful")
p5
helpfulness <- rm_prge %>%
select(session, help)
p6 <- ggplot(helpfulness, aes(session, help)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Reading Strategies",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
p6
```
```{r status, include=TRUE}
p4
```
### Perceived Effort
```{r effort, include=TRUE, fig.align="left"}
p5
```
### Perceived Strategy Helpfulness
```{r helpfulness, include=TRUE, fig.align="left"}
p6
```
# FALO Outcome
Column {.tabset data-width=650}
-----------------------------------------------------------------------
```{r falo measures data organization, include=FALSE}
head(outcome)
falo <- outcome %>%
filter(client == "FALO")
falo_brief_self <- brief_data %>%
filter(client == "FALO") %>%
select(client,
working_memory_pre_self,
working_memory_post_self,
plan_organize_pre_sr,
plan_organize_post_sr,
task_monitor_pre_sr,
task_monitor_post_sr) %>%
rename("WM Pre" = working_memory_pre_self,
"WM Post" = working_memory_post_self,
"PO Pre" = plan_organize_pre_sr,
"PO Post" = plan_organize_post_sr,
"TM Pre" = task_monitor_pre_sr,
"TM Post" = task_monitor_post_sr) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
falo_sr_brief <- c("WM Pre",
"WM Post",
"PO Pre",
"PO Post",
"TM Pre",
"TM Post")
falo_sr_plot <- ggplot(falo_brief_self, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = falo_sr_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Working Memory, Plan/Organize, and Task Monitoring Scales",
caption = "T-scores Above 65 are Clinically Significant")
falo_sr_plot
falo_brief_parent <- brief_data %>%
filter(client == "FALO") %>%
select(client,
working_memory_pre_parent,
working_memory_post_parent,
plan_organize_pre_parent,
plan_organize_post_parent,
task_monitor_pre_parent,
task_monitor_post_parent) %>%
rename("WM Pre" = working_memory_pre_parent,
"WM Post" = working_memory_post_parent,
"PO Pre" = plan_organize_pre_parent,
"PO Post" = plan_organize_post_parent,
"TM Pre" = task_monitor_pre_parent,
"TM Post" = task_monitor_post_parent) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
falo_parent_plot <- ggplot(falo_brief_parent, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = falo_sr_brief) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Working Memory, Plan/Organize, and Task Monitoring Scales",
caption = "T-scores Above 65 are Clinically Significant")
falo_parent_plot
class_falo <- falo %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
pcss_falo <- falo %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit_falo <- falo %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r falo plots, include=FALSE}
p8 <- ggplot(class_falo, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
p8
p9 <- ggplot(pcss_falo, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
geom_text(aes(measure, score, label = score),
nudge_y = -1,
color = "white") +
coord_flip() +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
p9
falo_pcss_table <- pcss_falo %>%
select(-client) %>%
gt() %>%
cols_label(measure = "PCSS Question",
score = "Response") %>%
cols_align(align = "left", columns = vars(measure)) %>%
cols_align(align = "center", columns = vars(score)) %>%
tab_header(title = "PCSS Results",
subtitle = "Cognitive Symptoms")
falo_pcss_table
falo_reactable <- pcss_falo %>%
select(-client) %>%
rename("PCSS Question" = measure,
"Response" = score) %>%
reactable()
falo_reactable
p10 <- ggplot(hit_falo, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning")
p10
```
### BRIEF Self Report
```{r falo brief, include=TRUE, fig.width=6}
falo_sr_plot
```
### BRIEF Parent Report
```{r falo brief parent, include=TRUE, fig.width=6}
falo_parent_plot
```
### CLASS
```{r falo class, include=TRUE, fig.width=6}
p8
```
### PCSS
```{r falo pcss, include=TRUE}
falo_pcss_table
```
### HIT
```{r falo hit, include=TRUE}
p10
```
Column {data-width=350}
-----------------------------------------------------------------------
### Client Demographics
```{r, include=FALSE}
head(outcome)
demo_falo <- outcome %>%
filter(client == "FALO") %>%
select(2:5)
head(demo_falo)
falo_table <- demo_falo %>%
gt() %>%
cols_label(sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression or Anxiety") %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
falo_table
```
```{r falo table, include=TRUE}
falo_table
```
# FALO Repeated
Column {.tabset data-width=650}
-----------------------------------------------------------------------
### Status Tracking 1
```{r falo repeated measures data cleaning, include=FALSE}
head(falo_rm)
falo_status_1 <- falo_rm %>%
select(session, status_1)
falo_status_1_plot <- ggplot(falo_status_1, aes(session, status_1)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 7),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Nights Per Week Gone to Bed Prior to 12:00 AM",
title = "Status Tracking Goal 1")
falo_status_1_plot
phone_falo <- falo_rm %>%
select(session, num_nights)
phone_falo_graph <- ggplot(phone_falo, aes(session, num_nights)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 7),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Nights Per Week Implementing No-Phone Strategy",
title = "No Phone Strategy",
subtitle = "To be implemented 1:00-7:00 AM")
phone_falo_graph
falo_effect <- falo_rm %>%
select(session, effect)
falo_effect_graph <- ggplot(falo_effect, aes(session, effect)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effectiveness",
title = "Perceived Effectiveness of No Phone Strategy",
caption = "1 = Not Effective at All\n 2 = Not Effective\n 3 = Somewhat Effective\n 4 = Effective\n 5 = Very Effective")
falo_effect_graph
falo_status_2 <- falo_rm %>%
select(session, status_2)
falo_status_2_plot <- ggplot(falo_status_2, aes(session, status_2)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(0 , 1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Missing Assignments per Week",
title = "Status Tracking Goal 2")
falo_status_2_plot
head(falo_rm)
falo_freq_1 <- falo_rm %>%
select(session, planner)
falo_freq_1_plot <- ggplot(falo_freq_1, aes(session, planner)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Weekly Assignments Entered into Calendar",
title = "Frequency of Planner Use")
falo_freq_1_plot
falo_help_1 <- falo_rm %>%
select(session, help_plan)
falo_planner_plot <- ggplot(falo_help_1, aes(session, help_plan)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Tracking Assignments in Planner",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
falo_planner_plot
falo_freq_2 <- falo_rm %>%
select(session, num_days)
falo_freq_2_plot <- ggplot(falo_freq_2, aes(session, num_days)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 7),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Days Per Week Using Time Block Strategy",
title = "Frequency of Time Block Strategy Use")
falo_freq_2_plot
falo_help_2 <- falo_rm %>%
select(session, help_block)
falo_block_plot <- ggplot(falo_help_2, aes(session, help_block)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Time Block Strategy",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
falo_block_plot
```
```{r falo status 1, include=TRUE}
falo_status_1_plot
```
### Phone Strategy Use
```{r falo phone graph, include=TRUE, fig.align="left"}
phone_falo_graph
```
### Perceived Effectiveness
```{r phone strategy helpfulness, include=TRUE, fig.align="left"}
falo_effect_graph
```
### Status Tracking 2
```{r falo status tracking 2, include=TRUE}
falo_status_2_plot
```
### Planner Use
```{r falo planner use, include=TRUE}
falo_freq_1_plot
```
### Planner Helpfulness
```{r falo planner helpfulness, include=TRUE}
falo_planner_plot
```
### Time Block Use
```{r falo time block use, include=TRUE}
falo_freq_2_plot
```
### Planner Helpfulness
```{r falo time block helpfulness, include=TRUE}
falo_block_plot
```
# DRKAT Outcome
Column {.tabset data-width=650}
-----------------------------------------------------------------------
```{r drkat measures data organization, include=FALSE}
head(outcome)
drkat_brief_2 <- brief_data %>%
filter(client == "DRKAT") %>%
select(client, 22, 23) %>%
rename("Working Memory Pre" = working_memory_pre_self,
"Working Memory Post" = working_memory_post_self) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
drkat <- outcome %>%
filter(client == "DRKAT")
brief_drkat <- drkat %>%
select(1, 16, 17, 20, 21, 32, 33) %>%
rename("Pre Global" = brief_global_pre_self,
"Post Global" = brief_global_post_self,
"Pre BRI" = brief_bri_pre_self,
"Post BRI" = brief_bri_post_self,
"Pre MI" = brief_mi_pre_self,
"Post MI" = brief_mi_post_self) %>%
pivot_longer(
cols = c(2:7),
names_to = "measure",
values_to = "score"
)
drkat_brief_graph <- c("Working Memory Pre", "Working Memory Post")
class_drkat <- drkat %>%
select(client, class_total_pre, class_total_post) %>%
rename("Pre Score" = class_total_pre,
"Post Score" = class_total_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
pcss_drkat <- drkat %>%
select(1, c(6:13)) %>%
rename("Feeling Slow Pre" = pcss_pre_feeling_slow,
"Feeling Slow Post" = pcss_post_feeling_slow,
"Feeling Foggy Pre" = pcss_pre_feeling_foggy,
"Feeling Foggy Post" = pcss_post_feeling_foggy,
"Difficulty Concentrating Pre" = pcss_pre_difficulty_concentrating,
"Difficulty Concentrating Post" = pcss_post_difficulty_concentrating,
"Difficulty Remembering Pre" = pcss_pre_difficulty_remembering,
"Difficulty Remembering Post" = pcss_post_difficulty_remembering) %>%
pivot_longer(
cols = c(2:9),
names_to = "measure",
values_to = "score"
)
hit_drkat <- drkat %>%
select(client, hit_pre, hit_post) %>%
rename("Pre Score" = hit_pre,
"Post Score" = hit_post) %>%
pivot_longer(
cols = c(2:3),
names_to = "measure",
values_to = "score"
)
```
```{r drkat plots, include=FALSE}
drkat_brief_plot <- ggplot(drkat_brief_2, aes(measure, score)) +
geom_hline(yintercept = 65,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = drkat_brief_graph) +
scale_y_continuous(limits = c(0, 100),
breaks = c(10, 20, 30, 40, 50, 60, 70, 80, 90, 100)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
plot.subtitle = element_text(color = "black", size = 10, face = "bold"),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "T-score",
title = "BRIEF Scores",
subtitle = "Working Memory Scale",
caption = "T-scores Above 65 are Clinically Significant")
drkat_brief_plot
drkat_class_plot <- ggplot(class_drkat, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = class_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "CLASS Scores")
drkat_class_plot
drkat_pcss_plot <- ggplot(pcss_drkat, aes(measure, score)) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = pcss_positions) +
scale_y_continuous(limits = c(0, 6),
breaks = c(0, 1, 2, 3, 4, 5, 6)) +
geom_text(aes(measure, score, label = score),
nudge_y = -1,
color = "white") +
coord_flip() +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "PCSS Results",
subtitle = "Cognitive Symptoms",
caption = "0 = No Symptoms\n 3 = Moderate Symptoms\n 6 = Severe Symptoms")
drkat_pcss_plot
drkat_hit_plot <- ggplot(hit_drkat, aes(measure, score)) +
geom_hline(yintercept = 50,
linetype = "dashed",
size = 1) +
geom_col(fill = "blue",
alpha = 0.7) +
scale_x_discrete(limits = hit_positions) +
scale_y_continuous(limits = c(0, 60),
breaks = c(10, 20, 30, 40, 50, 60)) +
geom_text(aes(measure, score, label = score),
nudge_y = -3,
color = "white") +
theme(panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "gray80")) +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10),
plot.caption = element_text(size = 10)) +
labs(x = "",
y = "Score",
title = "HIT Results",
caption = "Scores of 50 or Greater Suggest Headaches Significantly Impact Daily Functioning")
drkat_hit_plot
```
### BRIEF
```{r drkat brief, include=TRUE, fig.width=6}
drkat_brief_plot
```
### CLASS
```{r drkat class, include=TRUE, fig.width=6}
drkat_class_plot
```
### PCSS
```{r drkat pcss, include=TRUE}
drkat_pcss_plot
```
### HIT
```{r drkat hit, include=TRUE}
drkat_hit_plot
```
Column {data-width=350}
-----------------------------------------------------------------------
### Client Demographics
```{r, include=FALSE}
head(outcome)
demo_drkat <- outcome %>%
filter(client == "DRKAT") %>%
select(2:5)
head(demo_drkat)
drkat_table <- demo_drkat %>%
gt() %>%
cols_label(sex = "Sex",
age = "Age",
prev_mtbi = "Prior Concussions",
hx_depression = "History of Depression or Anxiety") %>%
cols_align(align = "center", columns = vars(sex, age, prev_mtbi, hx_depression)) %>%
tab_header(title = "Client Demographics")
drkat_table
```
```{r drkat table, include=TRUE}
drkat_table
```
# DRKAT Repeated
Column {.tabset data-width=650}
-----------------------------------------------------------------------
### Status Tracking
```{r repeated measures drkat data cleaning, include=FALSE}
head(rm_drkat)
drkat_track <- rm_drkat %>%
select(session, status)
drkat_status_plot <- ggplot(drkat_track, aes(session, status)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of House Chores Completed per Week",
title = "Status Tracking Goal")
drkat_status_plot
drkat_effort <- rm_drkat %>%
select(session, effort)
drkat_effort_plot <- ggplot(drkat_effort, aes(session, effort)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Effort",
title = "Perceived Effort While Completing House Chores",
caption = "1 = No Effort\n 2 = A little Effort\n 3 = Somewhat Effortful\n 4 = Quite Effortful\n 5 = Extremely Effortful")
drkat_motivation <- rm_drkat %>%
select(session, motivation)
drkat_motivation_plot <- ggplot(drkat_motivation, aes(session, motivation)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Motivation",
title = "Perceived Motivation to Complete House Chores",
caption = "1 = No Motivation\n 2 = A little Motivation\n 3 = Somewhat Motivated\n 4 = Quite Motivated\n 5 = Extremely Motivated")
drkat_freq <- rm_drkat %>%
select(session, frequency)
drkat_freq_plot <- ggplot(drkat_freq, aes(session, frequency)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 10),
breaks = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Number of Tasks Entered into Calendar per Week",
title = "Frequency of Calendar Use")
drkat_help <- rm_drkat %>%
select(session, helpfulness)
drkat_help_plot <- ggplot(drkat_help, aes(session, helpfulness)) +
geom_line() +
geom_point(size = 2) +
scale_x_continuous(limits = c(0, 10),
breaks = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) +
scale_y_continuous(limits = c(0, 5),
breaks = c(1, 2, 3, 4, 5)) +
theme_classic() +
theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
axis.text = element_text(size = 10),
axis.title=element_text(size=10),
strip.text = element_text(size = 10)) +
labs(x = "Session",
y = "Perceived Helpfulness",
title = "Perceived Helpfulness of Calendar",
caption = "1 = Not Helpful at All\n 2 = Not Helpful\n 3 = Somewhat Helpful\n 4 = Helpful\n 5 = Very Helpful")
```
```{r drkat status, include=TRUE}
drkat_status_plot
```
### Perceived Effort
```{r drkat perceived effort, include=TRUE}
drkat_effort_plot
```
### Perceived Motivation
```{r drkat perceived motivation, include=TRUE}
drkat_motivation_plot
```
### Planner Use
```{r drkat perceived frequency of strategy use, include=TRUE}
drkat_freq_plot
```
### Perceived Helpfulness
```{r drkat perceived helpfulness of strategy use, include=TRUE}
drkat_help_plot
```
